Main Objective
To assess the current state of recreational open spaces in Kumasi Metropolis and develop sustainable strategies for their management so as to ensure their long-term availability, effective and efficient use.
THE STATE AND SUSTAINABLE USE OF RECREATIONAL OPEN SPACES IN KUMASI METROPOLIS
Analysis
Laurens
June 09, 2025
Demographic profile
| Variable | Value | Count | Percentage |
|---|---|---|---|
| education_level | No Formal Education | 22 | 14.7 |
| education_level | Postgraduate | 28 | 18.7 |
| education_level | Primary | 17 | 11.3 |
| education_level | Secondary | 34 | 22.7 |
| education_level | Tertiary | 49 | 32.7 |
| gender | Female | 82 | 54.7 |
| gender | Male | 68 | 45.3 |
| occupation | Businessperson | 55 | 36.7 |
| occupation | Civil Servant | 48 | 32.0 |
| occupation | Private Sector Employee | 47 | 31.3 |
| Mean | SD | Median | Min | Max |
|---|---|---|---|---|
| 42.6 | 9.99 | 43 | 24 | 63 |
| Mean | SD | Median | Min | Max |
|---|---|---|---|---|
| 25.79 | 13.78 | 26 | 2 | 60 |
- Observations
Gender: Balanced distribution (Female: 82, 54.7%; Male: 68, 45.3%), ensuring equitable representation in ROS perceptions.
Age Distribution:
Histogram with Density: The histogram (bin width = 5 years) and density overlay show a distribution with a mean age of 42.6 years, median of 43 years, and range from 24 to 63 years.
The age distribution is slightly right-skewed, with most respondents aged 36–50 years (IQR: 36–50), indicating a mature adult population.
Middle-aged respondents may prioritize safety and functionality in ROS, influencing H1 (maintenance) and H2 (urbanization) findings.
Boxplot: The boxplot confirms a median age of ~43 years.
The sample is relatively homogeneous in age, centered around mid-adulthood.
Consistent age profile suggests uniform ROS usage patterns, supporting Objective 1.
Residence Length Distribution:
Histogram with Density : The histogram (bin width = 5 years) and density overlay show a mean residence length of 25.79 years, median of 26 years, and range from 2 to 60 years.
The distribution is right-skewed, with most respondents residing 14–33 years (IQR: 14.25–33), indicating a mix of long-term and newer residents.
Longer residency may correlate with stronger ROS attachment, relevant to H3 (management frameworks).
Boxplot: The boxplot shows a median of ~26 years.
The sample includes long-term residents, but some have resided for only a few years.
Varied residency durations may affect perceptions of ROS decline (H2, Objective 2).
Education Level Distribution:
Bar Plot: The bar plot shows 49 respondents (32.7%) with Tertiary education, 34 (22.7%) with Secondary, 28 (18.7%) with Postgraduate, 17 (11.3%) with Primary, and 22 (14.7%) with No Formal Education.
Finding: The sample is relatively educated, with over 50% having Secondary or higher education, and Tertiary being the most common level.
Implication: Higher education levels may drive awareness of sustainability issues (H3) and support for ROS policies (Objective 3), as educated respondents may advocate for better facilities or management.
Occupation Distribution:
Bar Plot: The bar plot shows 55 respondents (36.7%) are Businesspersons, 48 (32%) are Civil Servants, and 47 (31.3%) are Private Sector Employees.
Finding: The sample reflects a diverse occupational profile, with business and public/private sector employment nearly equally represented.
Implication: Occupational diversity suggests varied ROS usage patterns (e.g., Businesspersons may have less time for visits), informing engagement strategies (H3, Objective 3).
- Descriptive Analysis of Key Variables
| Variable | Category | Count | Percentage (%) |
|---|---|---|---|
| available_facilities | Benches and seating areas | 18 | 12.0 |
| Benches and seating areas Play equipment for children | 20 | 13.3 | |
| Benches and seating areas Play equipment for children Sports courts/fields | 13 | 8.7 | |
| Benches and seating areas Sports courts/fields | 12 | 8.0 | |
| Benches and seating areas Sports courts/fields Walking/jogging paths | 4 | 2.7 | |
| Play equipment for children | 40 | 26.7 | |
| Public restrooms | 5 | 3.3 | |
| Sports courts/fields | 24 | 16.0 | |
| Sports courts/fields Public restrooms | 2 | 1.3 | |
| Walking/jogging paths | 12 | 8.0 | |
| barriers_to_use | Distance from residential areas | 11 | 7.3 |
| High charges for entry | 3 | 2.0 | |
| Insecurity | 20 | 13.3 | |
| Lack of facilities | 116 | 77.3 | |
| choice_factors | None | 14 | 9.3 |
| Accessibility | 14 | 9.3 | |
| Accessibility Affordability | 3 | 2.0 | |
| Accessibility Availability of facilities | 10 | 6.7 | |
| Accessibility Proximity to residence | 5 | 3.3 | |
| Accessibility Safety and security | 2 | 1.3 | |
| Affordability | 12 | 8.0 | |
| Availability of facilities | 26 | 17.3 | |
| Availability of facilities Proximity to residence | 6 | 4.0 | |
| Availability of facilities Proximity to residence Affordability | 9 | 6.0 | |
| Others | 3 | 2.0 | |
| Proximity to residence | 13 | 8.7 | |
| Proximity to residence Affordability | 20 | 13.3 | |
| Safety and security | 5 | 3.3 | |
| Safety and security Affordability | 4 | 2.7 | |
| Unknown | 4 | 2.7 | |
| condition_ros | Abandoned and non-functional | 32 | 21.3 |
| Partially maintained but functional | 40 | 26.7 | |
| Poorly maintained with limited functionality | 58 | 38.7 | |
| Well-maintained and fully functional | 20 | 13.3 | |
| conversion_observed | No | 17 | 11.3 |
| Yes | 133 | 88.7 | |
| conversion_type | Others | 3 | 2.0 |
| Commercial land use | 70 | 46.7 | |
| Ghettos | 14 | 9.3 | |
| Industrial land use | 14 | 9.3 | |
| Residential land use | 43 | 28.7 | |
| Road expansion | 6 | 4.0 | |
| converted_ros | Parks and gardens | 62 | 41.3 |
| Playgrounds | 39 | 26.0 | |
| Public squares | 3 | 2.0 | |
| Sports fields | 23 | 15.3 | |
| None | 17 | 11.3 | |
| Multiple | 6 | 4.0 | |
| decline_noticed | No | 17 | 11.3 |
| Yes | 133 | 88.7 | |
| deterioration_cause | Unknown | 24 | 16.0 |
| Abandonments | 30 | 20.0 | |
| Encroachment for other land uses | 18 | 12.0 | |
| Lack of funding for recreational facilities | 13 | 8.7 | |
| Lack of priority for recreational spaces | 5 | 3.3 | |
| Poor maintenance | 39 | 26.0 | |
| Weak government policies | 21 | 14.0 | |
| education_level | No Formal Education | 22 | 14.7 |
| Postgraduate | 28 | 18.7 | |
| Primary | 17 | 11.3 | |
| Secondary | 34 | 22.7 | |
| Tertiary | 49 | 32.7 | |
| functionality_ros | Not functioning | 88 | 58.7 |
| Well functioning | 62 | 41.3 | |
| gender | Female | 82 | 54.7 |
| Male | 68 | 45.3 | |
| maintenance_responsibility | Community members | 49 | 32.7 |
| Local government | 89 | 59.3 | |
| Private investors | 12 | 8.0 | |
| occupation | Businessperson | 55 | 36.7 |
| Civil Servant | 48 | 32.0 | |
| Private Sector Employee | 47 | 31.3 | |
| priority_strategies | Community-led maintenance programs | 23 | 15.3 |
| Community-led maintenance programs Partnerships with NGOs and private organizations | 3 | 2.0 | |
| Improving government investment | 74 | 49.3 | |
| Increasing public awareness | 34 | 22.7 | |
| Increasing public awareness Improving government investment | 10 | 6.7 | |
| Increasing public awareness Improving government investment Community-led maintenance programs | 3 | 2.0 | |
| Partnerships with NGOs and private organizations | 3 | 2.0 | |
| ros_types_known | All | 33 | 22.0 |
| Parks and gardens | 19 | 12.7 | |
| Playgrounds | 20 | 13.3 | |
| Playgrounds, Sports fields | 10 | 6.7 | |
| Playgrounds, Sports fields, Parks and gardens | 20 | 13.3 | |
| Public squares | 6 | 4.0 | |
| Sports fields | 42 | 28.0 | |
| sustainability_measures | Community involvement in management | 7 | 4.7 |
| Community involvement in management Partnerships with private entities | 2 | 1.3 | |
| Regular maintenance by authorities | 82 | 54.7 | |
| Regular maintenance by authorities Community involvement in management | 2 | 1.3 | |
| Regular maintenance by authorities Stronger land-use policies/institutional frameworks | 7 | 4.7 | |
| Regular maintenance by authorities Stronger land-use policies/institutional frameworks Partnerships with private entities | 3 | 2.0 | |
| Stronger land-use policies/institutional frameworks | 44 | 29.3 | |
| Stronger land-use policies/institutional frameworks Community involvement in management Partnerships with private entities | 3 | 2.0 | |
| visit_frequency | Daily | 5 | 3.3 |
| Monthly | 49 | 32.7 | |
| Never | 14 | 9.3 | |
| Occasionally | 79 | 52.7 | |
| Weekly | 3 | 2.0 | |
| visited_ros | No | 14 | 9.3 |
| Yes | 136 | 90.7 | |
| visited_ros_types | Parks and gardens | 9 | 6.0 |
| Playgrounds | 24 | 16.0 | |
| Playgrounds, Sports fields | 31 | 20.7 | |
| Playgrounds, Sports fields, Parks and gardens | 5 | 3.3 | |
| Public squares | 6 | 4.0 | |
| Sports fields | 57 | 38.0 | |
| None | 18 | 12.0 |
| condition_ros | functionality_ros | Count |
|---|---|---|
| Abandoned and non-functional | Not functioning | 32 |
| Partially maintained but functional | Not functioning | 6 |
| Partially maintained but functional | Well functioning | 34 |
| Poorly maintained with limited functionality | Not functioning | 50 |
| Poorly maintained with limited functionality | Well functioning | 8 |
| Well-maintained and fully functional | Well functioning | 20 |
| Variable | Mean | Median | SD | Min | Max |
|---|---|---|---|---|---|
| safety_rating | 2.75 | 3 | 1.31 | 1 | 5 |
| support_community_participation | 4.35 | 5 | 1.00 | 1 | 5 |
| support_entrance_fee | 3.88 | 4 | 1.31 | 1 | 5 |
| support_preservation | 4.01 | 4 | 1.10 | 1 | 5 |
| Facility | Count | Percentage (%) |
|---|---|---|
| Play Equipment | 73 | 48.7 |
| Benches | 65 | 43.3 |
| Sports Courts | 55 | 36.7 |
| Paths | 16 | 10.7 |
| Restrooms | 7 | 4.7 |
| age | residence_length | safety_rating | support_entrance_fee | support_preservation | support_community_participation | |
|---|---|---|---|---|---|---|
| age | 1.00 | 0.84 | -0.09 | 0.16 | -0.01 | -0.11 |
| residence_length | 0.84 | 1.00 | 0.05 | 0.38 | 0.23 | 0.04 |
| safety_rating | -0.09 | 0.05 | 1.00 | 0.14 | 0.13 | 0.14 |
| support_entrance_fee | 0.16 | 0.38 | 0.14 | 1.00 | 0.52 | 0.37 |
| support_preservation | -0.01 | 0.23 | 0.13 | 0.52 | 1.00 | 0.57 |
| support_community_participation | -0.11 | 0.04 | 0.14 | 0.37 | 0.57 | 1.00 |
- Observations
Categorical Variables Summary (Table: Summary of Key Categorical Variables):
Gender: Balanced distribution (Female: 82, 54.7%; Male: 68, 45.3%), ensuring equitable representation in ROS perceptions.
Education Level: Highly educated sample (Tertiary: 49, 32.7%; Secondary: 34, 22.7%; Postgraduate: 28, 18.7%), with 14.7% having no formal education, suggesting awareness of ROS issues.
Visit Frequency: Most respondents visit ROS occasionally (79, 52.7%) or monthly (49, 32.7%), with few daily (5, 3.3%) or weekly (3, 2%) visitors, indicating low frequent engagement.
Safety Rating: Treated as categorical in some analyses, with moderate ratings (mean ~2.75, numerical summary), suggesting safety concerns.
Condition of ROS: Poorly maintained with limited functionality (58, 38.7%) and abandoned/non-functional (32, 21.3%) dominate, with only 20 (13.3%) well-maintained, highlighting decline (H1, H2).
Functionality of ROS: 88 (58.7%) ROS are not functioning, vs. 62 (41.3%) well-functioning.
Decline Noticed: 133 (88.7%) observed decline, with poor maintenance (39, 26%) and abandonments (30, 20%) as top causes, supporting H2.
Conversion Observed: 133 (88.7%) noted conversions, mostly to commercial (70, 46.7%) and residential (43, 28.7%) uses, confirming urbanization pressures (H2).
Barriers to Use: Lack of facilities (116, 77.3%) is the primary barrier, followed by insecurity (20, 13.3%), aligning with H2.
Maintenance Responsibility: Local government (89, 59.3%) is primarily responsible, followed by community members (49, 32.7%), indicating shared roles (H3).
Sustainability Measures: Regular maintenance (82, 54.7%) and stronger land-use policies (44, 29.3%) are top suggestions.
Implication: Poor ROS conditions, frequent conversions, and facility scarcity drive low engagement, but community and policy-driven solutions are favored (Objectives 2–3).
Numerical Variables Summary (Table: Summary of Numerical Variables):
Age: Mean ~42.6 years, median ~43, SD ~9.99, range 24–63, indicating a mature adult population.
Residence Length: Mean ~25.79 years, median ~26, SD ~13.78, range 2–60, showing a mix of long-term and newer residents.
Safety Rating: Mean ~2.75, median ~3, SD ~1.31, range 1–5, reflecting moderate safety perceptions.
Support for Entrance Fee: Mean ~3.88, median ~4, SD ~1.31, range 1–5, showing moderate support.
Support for Preservation: Mean ~4.01, median ~4, SD ~1.10, range 1–5, indicating strong support.
Support for Community Participation: Mean ~4.35, median ~5, SD ~1.00, range 1–5, reflecting high community enthusiasm.
Implication: Mature, long-residing respondents strongly support ROS preservation and participation, but moderate safety and fee support suggest barriers (H1, H3, Objective 3).
Available Facilities Prevalence (Table: Prevalence of Available Facilities):
Play Equipment: 73 (48.7%) respondents reported availability, the most common facility.
Benches: 65 (43.3%), followed by sports courts (55, 36.7%).
Paths: 16 (10.7%) and restrooms (7, 4.7%) are least common, indicating facility scarcity.
Implication: Limited availability of paths and restrooms aligns with barriers to use (H2), informing management priorities (Objective 3).
Visualizations:
Gender Distribution: Near-equal gender split (Female: 54.7%, Male: 45.3%), supporting equitable survey representation (Objective 1).
Visit Frequency: Occasional (52.7%) and monthly (32.7%) visits dominate, with few frequent visitors, suggesting low engagement (H3).
Safety Rating: Moderate ratings (mean ~2.75), with a spread across 1–5, indicating safety concerns (H1).
Condition vs. Functionality : Well-maintained ROS (20) are mostly well-functioning, while abandoned (32) and poorly maintained (58) are largely non-functional (88 total), supporting H1.
Facilities Prevalence: Play equipment and benches lead, with paths and restrooms rare, reinforcing facility gaps (H2).
Gender vs. Visit Frequency: Similar visit patterns across genders (e.g., ~50% occasional for both), suggesting gender-neutral engagement (H3).
Implication: Visuals confirm statistical summaries, highlighting maintenance and facility issues as key barriers to ROS use.
Correlation Matrix (Table: Correlation Matrix):
Strong Correlation: Age and residence length (r = 0.84), as older respondents tend to have lived longer in Kumasi.
Moderate Correlations: Support for preservation and community participation (r = 0.57), preservation and entrance fee (r = 0.52), indicating aligned attitudes toward ROS support (H3).
Weak Correlations: Safety rating with support variables (r ~0.13–0.14), residence length with entrance fee (r = 0.38), suggesting limited demographic influence on perceptions.
Negative/Negligible: Age with safety/support variables (r ~ -0.11 to 0.16), indicating age has minimal impact on ROS attitudes.
Implication: Strong support correlations suggest community-driven initiatives could enhance engagement, while weak safety correlations highlight external factors (e.g., maintenance, H1).
Objective 1: Physical state & functionality
To evaluate the physical state and functionality of existing recreational open spaces in Kumasi.
This section present the physical condition, functionality, safety ratings, and facility availability of recreational open spaces (ROS) in addressing Objective 1.
| Conduction | Count | Percentage (%) |
|---|---|---|
| Abandoned and non-functional | 32 | 21.3% |
| Partially maintained but functional | 40 | 26.7% |
| Poorly maintained with limited functionality | 58 | 38.7% |
| Well-maintained and fully functional | 20 | 13.3% |
| Statistic | Value |
|---|---|
| Mean | 2.75 |
| SD | 1.31 |
| Min | 1.00 |
| Max | 5.00 |
| Facility Type | Count | Percentage (%) |
|---|---|---|
| Play equipment for children | 40 | 26.7% |
| Sports courts/fields | 24 | 16.0% |
| Benches and seating areas Play equipment for children | 20 | 13.3% |
| Benches and seating areas | 18 | 12.0% |
| Benches and seating areas Play equipment for children Sports courts/fields | 13 | 8.7% |
| Benches and seating areas Sports courts/fields | 12 | 8.0% |
| Walking/jogging paths | 12 | 8.0% |
| Public restrooms | 5 | 3.3% |
| Benches and seating areas Sports courts/fields Walking/jogging paths | 4 | 2.7% |
| Sports courts/fields Public restrooms | 2 | 1.3% |
- Observations for Objective 1
Physical Condition of ROS (Table: Distribution of ROS Physical Condition; Plot: p_condition):
Observation: The most common ROS condition is “Poorly maintained with limited functionality” (58 respondents, 38.7%), followed by “Partially maintained but functional” (40, 26.7%), “Abandoned and non-functional” (32, 21.3%), and “Well-maintained and fully functional” (20, 13.3%).
Finding: A significant majority (80%, 58 + 32 = 90 respondents) report ROS as poorly maintained or abandoned, with only 13.3% perceiving ROS as well-maintained.
Implication for Objective 1: The prevalent poor condition of ROS likely negatively influences residents’ perceptions, reducing usage and satisfaction. This aligns with demographic characteristics (e.g., educated respondents from the previous analyses) who may expect better maintenance, highlighting a need for improved upkeep to enhance perceptions.
Functionality of ROS (Table: Distribution of ROS Functionality; Plots: p_functionality, p_functionality_count):
Observation: 88 respondents (58.7%) report ROS as “Not functioning,” while 62 (41.3%) report “Well functioning.”
Finding: Over half of ROS are perceived as non-functional, corroborating the poor physical condition findings.
Implication for Objective 1: Non-functionality significantly shapes negative resident perceptions, particularly among active users (e.g., 90.7% visited ROS, previous analyses). This suggests that functionality is a critical factor in how demographics (e.g., age, occupation) perceive ROS quality, emphasizing the need for functional improvements.
Safety Ratings of ROS (Table: Summary Statistics for Safety Ratings; Plot: p_safety):
Observation: Safety ratings have a mean of 2.75, median of 3, standard deviation of 1.31, and range from 1 (Poor) to 5 (Excellent).
Finding: Residents perceive ROS safety as moderate, with variability indicating mixed experiences. The boxplot likely shows a central tendency around 2–4.
Implication for Objective 1: Moderate safety ratings suggest safety concerns influence perceptions, particularly for demographics like females (54.7% of sample) or older respondents (mean age ~43), who may prioritize security. Improving safety could enhance positive perceptions across demographic groups.
Available Facilities in ROS (Table: Distribution of Available Facilities; Plots: p_facilities_count, p_facility_pct):
Observation: The most reported facility is “Play equipment for children” (40, 26.7%), followed by “Sports courts/fields” (24, 16%), and combinations like “Benches and seating areas + Play equipment” (20, 13.3%). Binary variables show play equipment (48.7%), benches (43.3%), and sports courts (36.7%) as most prevalent, with paths (10.7%) and restrooms (4.7%) least common.
Finding: While play equipment and benches are relatively available, critical amenities like paths and restrooms are scarce, limiting ROS appeal.
Implication for Objective 1: Facility scarcity, especially restrooms and paths, negatively impacts perceptions, particularly for demographics like businesspersons (36.7%) or families (likely younger respondents) who need diverse amenities. Enhancing facility variety could improve perceptions and usage.
-Summary
ROS Conditions and Perceptions: The majority of ROS are poorly maintained (38.7%) or abandoned (21.3%), non-functional (58.7%), and moderately safe (mean ~2.75), with limited facilities (e.g., only 4.7% report restrooms). These conditions likely foster negative perceptions among residents, reducing engagement (e.g., 52.7% visit occasionally).
Demographic Influence: The sample’s characteristics (balanced gender, mean age ~43, high education [32.7% Tertiary], diverse occupations) suggest educated, mature respondents are critical of ROS conditions, with safety and facility availability shaping their perceptions. For example, females or older residents may prioritize safety, while businesspersons may value accessible facilities.
These findings highlight how poor ROS conditions (physical state, functionality, safety, facilities) influence resident perceptions, particularly across demographics. Improving maintenance, functionality, safety, and facility diversity is critical to enhance positive perceptions and meet Objective 1’s goal of evaluating influencing factors.
Links to hypotheses: H1 (Maintenance): Poor maintenance and non-functionality drive negative perceptions, supporting the need for upkeep improvements.
H2 (Urbanization): Facility scarcity (e.g., restrooms) reflects urbanization pressures, impacting perceptions.
H3 (Management): Addressing these conditions through community-driven frameworks (noted in previous analyses) could improve perceptions.
Objective 2: Factors Contributing to Decline
To investigate the factors contributing to the decline of recreational open spaces in Kumasi.
| Decline Noticed | Count | Percentage (%) |
|---|---|---|
| No | 17 | 11.3 |
| Yes | 133 | 88.7 |
| Cause of Deterioration | Count | Percentage (%) |
|---|---|---|
| Abandonments | 30 | 20.0 |
| Encroachment for other land uses | 18 | 12.0 |
| Lack of funding for recreational facilities | 13 | 8.7 |
| Lack of priority for recreational spaces | 5 | 3.3 |
| Poor maintenance | 39 | 26.0 |
| Unknown | 24 | 16.0 |
| Weak government policies | 21 | 14.0 |
| Conversion Observed | Count | Percentage (%) |
|---|---|---|
| No | 17 | 11.3 |
| Yes | 133 | 88.7 |
| Conversion Type | Count | Percentage (%) |
|---|---|---|
| Commercial land use | 70 | 52.6 |
| Ghettos | 14 | 10.5 |
| Industrial land use | 4 | 3.0 |
| Others | 3 | 2.3 |
| Residential land use | 36 | 27.1 |
| Road expansion | 6 | 4.5 |
| Barrier to Use | Count | Percentage (%) |
|---|---|---|
| Distance from residential areas | 11 | 7.3 |
| High charges for entry | 3 | 2.0 |
| Insecurity | 20 | 13.3 |
| Lack of facilities | 116 | 77.3 |
| Decline Noticed | Conversion Observed: No | Conversion Observed: Yes |
|---|---|---|
| No | 17 (100.0%) | 0 (0.0%) |
| Yes | 0 (0.0%) | 133 (100.0%) |
| Cause of Deterioration | Count | Percentage (%) |
|---|---|---|
| Abandonments | 30 | 22.6 |
| Encroachment for other land uses | 18 | 13.5 |
| Lack of funding for recreational facilities | 13 | 9.8 |
| Lack of priority for recreational spaces | 5 | 3.8 |
| Poor maintenance | 39 | 29.3 |
| Unknown | 7 | 5.3 |
| Weak government policies | 21 | 15.8 |
- Observations for Objective 2
Perceived ROS Decline ( Distribution of Perceived ROS Decline; Plot: p_decline):
Observation: 133 respondents (88.7%) noticed a decline in ROS, while 17 (11.3%) did not.
Finding: The vast majority of residents perceive a significant decline in ROS, indicating widespread recognition of deterioration.
Implication for Objective 2: The high prevalence of perceived decline confirms that ROS degradation is a critical issue, setting the stage for identifying specific contributing factors like maintenadwnce and land-use changes.
Causes of ROS Deterioration (TReported Causes of ROS Deterioration; Plot: p_deterioration):
Observation: The leading cause is poor maintenance (39, 26.0%), followed by abandonments (30, 20.0%), unknown causes (24, 16.0%), weak government policies (21, 14.0%), encroachment for other land uses (18, 12.0%), lack of funding (13, 8.7%), and lack of priority for recreational spaces (5, 3.3%).
Finding: Poor maintenance and abandonment are the dominant drivers of ROS decline, with policy and funding issues also significant.
Implication for Objective 2: Maintenance neglect and abandonment are primary factors, worsen by weak policies and funding shortages, suggesting actionable areas for intervention to curb decline.
Observed ROS Conversions ( Distribution of Observed ROS Conversions; Plot: p_conversion):
Observation: 133 respondents (88.7%) observed ROS conversions, while 17 (11.3%) did not.
Finding: Conversions are nearly as prevalent as perceived decline, indicating significant land-use changes affecting ROS.
Implication for Objective 2: The high rate of conversions points to urbanization pressures as a key contributor to ROS decline.
Types of ROS Conversions (Table 8: Types of ROS Conversions; Plot: p_conversion_type):
Observation: Among the 133 respondents who observed conversions, commercial land use (70, 52.6%) and residential land use (36, 27.1%) are the most common, followed by ghettos (14, 10.5%), road expansion (6, 4.5%), industrial land use (4, 3.0%), and others (3, 2.3%).
Finding: Commercial and residential developments dominate ROS conversions, reflecting urban expansion priorities.
Implication for Objective 2: Urbanization-driven conversions, particularly for commercial and residential purposes, are a major factor in ROS decline, reducing available recreational space.
Barriers to ROS Use (Table: Reported Barriers to ROS Use; Plot: p_barriers):
Observation: Lack of facilities (116, 77.3%) is the primary barrier, followed by insecurity (20, 13.3%), distance from residential areas (11, 7.3%), and high entry charges (3, 2.0%).
Finding: Facility scarcity overwhelmingly limits ROS usage, with safety concerns also notable.
Implication for Objective 2: The absence of adequate facilities, linked to maintenance neglect and conversions, significantly contributes to ROS decline by deterring usage and diminishing functionality.
Relationship Between Decline and Conversion (Cross-Tabulation of Decline Noticed and Conversion Observed; Table 11: Chi-Square Test):
Observation: All 133 respondents who noticed decline also observed conversions (100%), while all 17 who did not notice decline reported no conversions (100%). The chi-square test yields a statistic of 140.21, p-value ~0, indicating a strong association ( though small cell counts).
Finding: There is a near-perfect correlation between perceiving ROS decline and observing conversions, suggesting conversions are a key driver of decline.
Implication for Objective 2: Conversions are strongly linked to perceived decline, reinforcing urbanization as a central factor in ROS deterioration.
Causes of Deterioration Among Converted ROS (Table: Causes of Deterioration Among Converted ROS):
Observation: Among the 133 converted ROS, poor maintenance (39, 29.3%) and abandonments (30, 22.6%) remain top causes, followed by weak government policies (21, 15.8%), encroachment (18, 13.5%), lack of funding (13, 9.8%), unknown (7, 5.3%), and lack of priority (5, 3.8%).
Finding: Even among converted ROS, maintenance neglect and abandonment dominate, with policy and encroachment issues significant.
Implication for Objective 2: The persistence of maintenance and policy-related causes in converted ROS highlights that conversions exacerbate existing neglect, amplifying decline.
- Summary
Factors Contributing to Decline: The primary factors driving ROS decline are poor maintenance (26.0%), abandonment (20.0%), and conversions to commercial (52.6%) and residential (27.1%) land uses, with weak government policies (14.0%) and lack of funding (8.7%) as secondary contributors. Lack of facilities (77.3%) is the dominant barrier to use, further reducing ROS functionality.
Urbanization Pressures: The near-universal observation of conversions (88.7%) and their strong association with decline (chi-square p ~0) confirm urbanization as a central driver, particularly through commercial and residential developments.
These findindgs identify maintenance neglect, abandonment, urbanization-driven conversions, and facility scarcity as key contributors to ROS decline. Policy and funding gaps exacerbawte these issues, suggesting a need for stronger governance and investment.
Links to hypotheses: H1 (Maintenance): Poor maintenance (26.0%) and abandonment (20.0%) align with non-functionality (58.7%, previous analyses), driving decline.
H2 (Urbanization): Conversions (88.7%) and encroachment (12.0%) confirm urbanization’s role in reducing ROS availability.
H3 (Management): Weak policies (14.0%) and funding shortages (8.7%) highlight governance issues to address in management frameworks.
Objective 3: Sustainable management frameworks
To identify sustainable management frameworks for the development and preservation of recreational open spaces in the Kumasi.
| Sustainability Measure | Count | Percentage (%) |
|---|---|---|
| Regular maintenance by authorities | 82 | 54.7 |
| Stronger land-use policies/institutional frameworks | 44 | 29.3 |
| Community involvement in management | 7 | 4.7 |
| Regular maintenance by authorities Stronger land-use policies/institutional frameworks | 7 | 4.7 |
| Regular maintenance by authorities Stronger land-use policies/institutional frameworks Partnerships with private entities | 3 | 2.0 |
| Stronger land-use policies/institutional frameworks Community involvement in management Partnerships with private entities | 3 | 2.0 |
| Community involvement in management Partnerships with private entities | 2 | 1.3 |
| Regular maintenance by authorities Community involvement in management | 2 | 1.3 |
| Maintenance Responsibility | Count | Percentage (%) |
|---|---|---|
| Community members | 49 | 32.7 |
| Local government | 89 | 59.3 |
| Private investors | 12 | 8.0 |
| Sustainability Measure | Percentage Supporting (%) |
|---|---|
| Community | 9.3 |
| Maintenance | 62.7 |
| Partnerships | 5.3 |
| Policies | 38.0 |
| Management Measure | Count | Percentage (%) |
|---|---|---|
| Maintenance | 94 | 54.3 |
| Policies | 57 | 32.9 |
| Community | 14 | 8.1 |
| Partnerships | 8 | 4.6 |
| Priority Strategy | Count | Percentage (%) |
|---|---|---|
| Improving government investment | 74 | 49.3 |
| Increasing public awareness | 34 | 22.7 |
| Community-led maintenance programs | 23 | 15.3 |
| Increasing public awareness Improving government investment | 10 | 6.7 |
| Community-led maintenance programs Partnerships with NGOs and private organizations | 3 | 2.0 |
| Increasing public awareness Improving government investment Community-led maintenance programs | 3 | 2.0 |
| Partnerships with NGOs and private organizations | 3 | 2.0 |
| Sustainability Strategy | Count | Percentage (%) |
|---|---|---|
| Gov Investment | 87 | 51.5 |
| Awareness | 47 | 27.8 |
| Community Programs | 29 | 17.2 |
| Ngo Partnerships | 6 | 3.6 |
| Management Option | Rating (1–5) | Count | Percentage (%) |
|---|---|---|---|
| Community Participation | 1 | 2 | 0.4 |
| Community Participation | 2 | 6 | 1.3 |
| Community Participation | 3 | 28 | 6.2 |
| Community Participation | 4 | 15 | 3.3 |
| Community Participation | 5 | 99 | 22.0 |
| Entrance Fee | 1 | 12 | 2.7 |
| Entrance Fee | 2 | 15 | 3.3 |
| Entrance Fee | 3 | 21 | 4.7 |
| Entrance Fee | 4 | 33 | 7.3 |
| Entrance Fee | 5 | 69 | 15.3 |
| Preservation | 1 | 7 | 1.6 |
| Preservation | 2 | 10 | 2.2 |
| Preservation | 3 | 18 | 4.0 |
| Preservation | 4 | 55 | 12.2 |
| Preservation | 5 | 60 | 13.3 |
| Management Option | Average Rating (1–5) |
|---|---|
| Support for Entrance Fee | 3.88 |
| Support for Preservation | 4.01 |
| Support for Community Participation | 4.35 |
- Observations for Objective 3
Preferred Sustainability Measures ( Distribution of Preferred Sustainability Measures; Percentage Supporting Sustainability Measures):
Observation: Regular maintenance by authorities is the most preferred measure (82 respondents, 54.7%), followed by stronger land-use policies/institutional frameworks (44, 29.3%). Community involvement (7, 4.7%) and partnerships with private entities (combined in multi-select responses, ~5.3%) are less favored. Binary variables show maintenance supported by 62.7%, policies by 38.0%, community involvement by 9.3%, and partnerships by 5.3%.
Finding: Residents strongly prioritize authority-led maintenance and robust land-use policies, with limited support for community or private involvement.
Implication for Objective 3: Sustainable frameworks should emphasize government-led maintenance and policy enforcement, aligning with resident expectations for institutional action to enhance ROS.
Perceived Maintenance Responsibility ( Perceived Responsibility for ROS Maintenance; Plot: p_maintenance):
Observation: Local government is seen as primarily responsible (89 respondents, 59.3%), followed by community members (49, 32.7%) and private investors (12, 8.0%).
Finding: Residents predominantly expect local government to lead maintenance efforts, though a significant minority supports community involvement.
Implication for Objective 3: Management frameworks should center on local government leadership, with community participation as a complementary strategy to ensure accountability and engagement.
Proposed Management Measures (Table 16: Proposed Management Measures):
Observation: Maintenance is the top proposed measure (94 respondents, 54.3%), followed by policies (57, 32.9%), community involvement (14, 8.1%), and partnerships (8, 4.6%).
Finding: Maintenance and policy-focused measures dominate, reinforcing the preference for institutional solutions over community or private roles.
Implication for Objective 3: Frameworks should prioritize regular maintenance and policy reforms, with community and private roles as secondary supports.
Priority Strategies for ROS Management ( Priority Strategies; Table 18: Endorsed Sustainability Strategies; Plot: p_strategies):
Observation: Improving government investment is the top strategy (74 respondents, 49.3%; 87 endorsements, 51.5%), followed by increasing public awareness (34, 22.7%; 47, 27.8%), community-led maintenance programs (23, 15.3%; 29, 17.2%), and NGO/private partnerships (3, 2.0%; 6, 3.6%). Multi-select responses add minor support for combined strategies.
Finding: Government investment and public awareness are the most endorsed strategies, with community programs moderately supported and NGO partnerships least favored.
Implication for Objective 3: Sustainable frameworks should focus on securing government funding and raising awareness, with community programs as a viable but less prioritized option, ensuring broad resident buy-in.
Support Levels for Management Options (Table 19: Support Levels for ROS Management Options; Table 20: Average Support; Plot: p_support_metrics):
Observation: Support for community participation has the highest average rating (4.35, with 99 respondents rating 5, 22.0%), followed by preservation (4.01, 60 rating 5, 13.3%) and entrance fees (3.88, 69 rating 5, 15.3%). Most respondents rate these options 4 or 5, indicating strong support.
Finding: Residents strongly support community participation and preservation, with moderate support for entrance fees, suggesting willingness to engage in and fund ROS sustainability.
Implication for Objective 3: Frameworks should leverage high community enthusiasm (mean ~4.35) and preservation support (mean ~4.01), with entrance fees as a potential but less popular funding mechanism.
-Summary
Sustainable Management Frameworks: Residents prioritize government-led solutions, including regular maintenance (54.7%, 62.7% support), stronger land-use policies (29.3%, 38.0% support), and increased government investment (49.3%, 51.5% endorsements). Local government is seen as primarily responsible (59.3%), with community involvement (32.7%, 9.3% support) as a secondary but valued role. Public awareness (22.7%, 27.8%) and community programs (15.3%, 17.2%) are moderately supported, while private/NGO partnerships (2.0%, 3.6%) are least favored.
Resident Support: High ratings for community participation (mean ~4.35) and preservation (mean ~4.01) indicate strong resident willingness to engage, with entrance fees (mean ~3.88) less preferred but viable. This suggests frameworks should combine institutional action with community engagement.
These findings address Objective 3 by proposing a framework centered on government-led maintenance and policy enforcement, supported by community participation and awareness campaigns, with funding from government investment and potentially entrance fees. Private partnerships are less critical.
Links to hypotheses:
H1 (Maintenance): Strong support for maintenance (62.7%) aligns with addressing poor maintenance as a decline factor (Objective 2).
H2 (Urbanization): Policy support (38.0%) addresses conversions (88.7%, Objective 2) through stronger land-use frameworks.
H3 (Management): Government investment (51.5%) and community participation (mean ~4.35) support effective, resident-backed management strategies.
Cross-objective analysis
| Physical Condition | Functionality | Count | Percentage (%) |
|---|---|---|---|
| Abandoned and non-functional | Not functioning | 32 | 100.0 |
| Partially maintained but functional | Not functioning | 6 | 15.0 |
| Partially maintained but functional | Well functioning | 34 | 85.0 |
| Poorly maintained with limited functionality | Not functioning | 50 | 86.2 |
| Poorly maintained with limited functionality | Well functioning | 8 | 13.8 |
| Well-maintained and fully functional | Well functioning | 20 | 100.0 |
| Safety Rating (1–5) | Count | Percentage (%) |
|---|---|---|
| 1 | 29 | 19.3 |
| 2 | 44 | 29.3 |
| 3 | 33 | 22.0 |
| 4 | 24 | 16.0 |
| 5 | 20 | 13.3 |
-Observations
Relationship Between Physical Condition and Functionality (Table 21: Cross-Tabulation of ROS Physical Condition and Functionality; Plot: Condition vs. Functionality):
Observation: Abandoned and non-functional ROS are entirely non-functioning (32 respondents, 100%).
Partially maintained but functional ROS are mostly well-functioning (34, 85.0%), with 6 (15.0%) non-functioning.
Poorly maintained with limited functionality ROS are predominantly non-functioning (50, 86.2%), with 8 (13.8%) well-functioning.
Well-maintained and fully functional ROS are entirely well-functioning (20, 100%).
Finding: Physical condition strongly correlates with functionality. Abandoned (21.3%) and poorly maintained (38.7%) ROS are overwhelmingly non-functioning (82/90, 91.1%), while well-maintained ROS are fully functional. Partially maintained ROS show mixed functionality, leaning toward well-functioning.
Implications:
Objective 1: Poor physical conditions (60% abandoned or poorly maintained) and non-functionality (58.7% overall, previous analyses) negatively shape resident perceptions, particularly among educated (32.7% Tertiary) or mature (mean age ~43) demographics who may expect better quality.
Objective 2: Poor maintenance and abandonment, driving non-functionality, are key decline factors, reinforcing earlier findings (26.0% cite poor maintenance, 20.0% abandonment).
Objective 3: Management frameworks should prioritize maintenance to restore functionality, as well-maintained ROS are perceived as fully functional, aligning with resident preferences for regular maintenance (54.7%).
Safety Ratings of ROS (Table 22: Distribution of Safety Ratings; Plot: Safety Ratings):
Observation: Safety ratings are distributed as follows: 1 (Very Unsafe, 29, 19.3%), 2 (44, 29.3%), 3 (33, 22.0%), 4 (24, 16.0%), 5 (Very Safe, 20, 13.3%). The mean is ~2.75 (previous analyses), with a peak at rating 2 (29.3%).
Finding: Safety perceptions are moderate to low, with 48.6% (73 respondents) rating ROS as unsafe or very unsafe (1 or 2), and only 29.3% (44) rating them safe or very safe (4 or 5). The spread indicates varied experiences.
Implications:
Objective 1: Low safety ratings negatively influence perceptions, especially for demographics like females (54.7%) or older respondents who may prioritize security, reducing ROS usage (52.7% visit occasionally).
Objective 2: Insecurity as a barrier (13.3%, previous analyses) and low safety ratings suggest safety issues contribute to decline by deterring use, alongside maintenance and conversions (88.7%).
Objective 3: Management frameworks should enhance safety measures (e.g., lighting, security), aligning with community participation (mean rating ~4.35) to improve perceptions and usage.
-Summary
Objective 1 (Perceptions): Poor physical conditions (60% abandoned or poorly maintained) and non-functionality (91.1% of abandoned/poorly maintained ROS) drive negative perceptions, compounded by low safety ratings (48.6% unsafe/very unsafe). These factors likely reduce engagement across demographics (e.g., educated, mature residents).
Objective 2 (Decline): Non-functionality, linked to poor maintenance (86.2% of poorly maintained ROS) and abandonment (100% of abandoned ROS), alongside safety concerns, confirms maintenance neglect and insecurity as decline factors, supporting earlier findings (26.0% poor maintenance, 13.3% insecurity).
Objective 3 (Management): Restoring functionality through maintenance (preferred by 54.7%) and improving safety (aligned with community participation support, mean ~4.35) are critical for sustainable frameworks, addressing resident priorities for government-led action (59.3% expect local government responsibility).
Statistical Tests Begins Here
##
## Abandoned and non-functional Partially maintained but functional
## Female 20 19
## Male 12 21
##
## Poorly maintained with limited functionality
## Female 24
## Male 34
##
## Well-maintained and fully functional
## Female 19
## Male 1##
## Pearson's Chi-squared test
##
## data: table(df$gender, df$condition_ros)
## X-squared = 18.882, df = 3, p-value = 0.0002892##
## Welch Two Sample t-test
##
## data: safety_rating by gender
## t = 4.1752, df = 138.24, p-value = 5.24e-05
## alternative hypothesis: true difference in means between group Female and group Male is not equal to 0
## 95 percent confidence interval:
## 0.4499572 1.2595119
## sample estimates:
## mean in group Female mean in group Male
## 3.134146 2.279412##
## Call:
## lm(formula = safety_rating ~ age + gender + residence_length +
## education_level, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.5807 -0.8960 -0.1472 0.8645 3.0738
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.15008 0.63461 6.540 1.04e-09 ***
## age -0.05077 0.01864 -2.724 0.00727 **
## genderMale -0.75837 0.20409 -3.716 0.00029 ***
## residence_length 0.03988 0.01328 3.004 0.00315 **
## education_levelPostgraduate 0.49359 0.35831 1.378 0.17051
## education_levelPrimary 0.29331 0.39205 0.748 0.45561
## education_levelSecondary -0.13054 0.33489 -0.390 0.69726
## education_levelTertiary -0.06405 0.31387 -0.204 0.83859
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.205 on 142 degrees of freedom
## Multiple R-squared: 0.1891, Adjusted R-squared: 0.1491
## F-statistic: 4.731 on 7 and 142 DF, p-value: 8.447e-05-Observations
Gender and ROS Physical Condition ( Cross-Tabulation; Table 24: Chi-Square Test):
Observation: Females (N=82): 20 (24.4%) report abandoned, 19 (23.2%) partially maintained, 24 (29.3%) poorly maintained, 19 (23.2%) well-maintained.
Males (N=68): 12 (17.6%) abandoned, 21 (30.9%) partially maintained, 34 (50.0%) poorly maintained, 1 (1.5%) well-maintained.
Chi-square test: χ² = 18.88, df = 3, p < 0.001, indicating a significant association.
Finding: Males are more likely to perceive ROS as poorly maintained (50.0% vs. 29.3%), while females report higher proportions of well-maintained (23.2% vs. 1.5%) and abandoned (24.4% vs. 17.6%) ROS. The significant association suggests gender influences perceptions of ROS condition.
Implications:
Objective 1: Gender shapes ROS perceptions, with males more critical of maintenance, potentially due to usage patterns (e.g., males may visit sports fields, 38.0%). This informs demographic-specific perceptions.
Objective 2: Higher male reporting of poor maintenance (50.0%) reinforces maintenance neglect as a decline factor (26.0%, previous analyses).
Objective 3: Management frameworks should address gender-specific perceptions, emphasizing maintenance to align with male concerns and leveraging female optimism for well-maintained ROS.
Safety Ratings by Gender: Observation: T-test: t = 4.18, df = 138.2, p < 0.001, mean difference = 0.85 (males higher), 95% CI [0.45, 1.26].
Table 28: Females’ safety ratings: 6 (7.3%) rate 1, 22 (26.8%) rate 2, 22 (26.8%) rate 3, 19 (23.2%) rate 4, 13 (15.9%) rate 5. Males: 23 (33.8%) rate 1, 22 (32.4%) rate 2, 11 (16.2%) rate 3, 5 (7.4%) rate 4, 7 (10.3%) rate 5. P < 0.001 for gender difference.
Finding: Males report significantly lower safety perceptions (33.8% rate 1 vs. 7.3% for females), with females more likely to give moderate-to-high ratings (4 or 5: 39.1% vs. 17.7%). The mean difference suggests males perceive ROS as less safe.
Implications:
Objective 1: Gender significantly influences safety perceptions, with males’ lower ratings potentially reducing usage, particularly for demographics like businesspersons (36.7%) who may avoid unsafe ROS.
Objective 2: Low male safety ratings align with insecurity as a barrier (13.3%), contributing to ROS decline by deterring use.
Objective 3: Frameworks should prioritize safety enhancements (e.g., lighting, patrols) to address male concerns, aligning with community participation support (mean ~4.35).
Linear Regression for Safety Rating ( Linear Regression):
Observation:
Significant predictors: Age (β = -0.05, p = 0.007), Gender (Male, β = -0.76, p < 0.001), Residence Length (β = 0.04, p = 0.003).
Non-significant: Education levels (p > 0.17).
Model fit: R² = 0.189, Adjusted R² = 0.149, F = 4.73, p < 0.001.
Finding: Males and older respondents report lower safety ratings, while longer residency is associated with slightly higher ratings. Education level has no significant effect. The model explains ~18.9% of variance in safety ratings.
Implications:
Objective 1: Gender and age influence safety perceptions, with males and older residents more critical, guiding demographic-targeted interventions.
Objective 2: Lower safety perceptions among males and older residents reinforce insecurity as a decline factor, reducing ROS usage.
Objective 3: Frameworks should address safety for males and older residents, leveraging community participation (mean ~4.35) to enhance perceptions.
Hypothesis 1
H1: Adequate maintenance of ROS in Kumasi reduces the rate of facility deterioration and increases functionality.
This hypothesis suggest that ROS with regular maintenance ( via sustainability_measures like “Regular maintenance by authorities”) have lower deterioration rates (e.g., less “Poor maintenance” in deterioration_cause) and higher functionality (e.g., functionality_ros = “Well functioning”).
H0: Adequate maintenance has no effect on facility deterioration or functionality.
H1: Adequate maintenance reduces deterioration and increases functionality.
##
## Pearson's Chi-squared test
##
## data: table(df$measure_maintenance, df$deterioration_cause)
## X-squared = 40.902, df = 6, p-value = 3.028e-07##
## Pearson's Chi-squared test with Yates' continuity correction
##
## data: table(df$measure_maintenance, df$functionality_ros)
## X-squared = 2.5373, df = 1, p-value = 0.1112##
## Call:
## glm(formula = functionality_binary ~ maintenance_binary + maintenance_responsibility +
## gender + age, family = binomial, data = df)
##
## Coefficients:
## Estimate Std. Error z value
## (Intercept) 2.85353 0.89368 3.193
## maintenance_binary 0.70619 0.39929 1.769
## maintenance_responsibilityLocal government -0.60767 0.40031 -1.518
## maintenance_responsibilityPrivate investors 0.17362 0.72369 0.240
## genderMale -0.44929 0.36958 -1.216
## age -0.07427 0.02000 -3.713
## Pr(>|z|)
## (Intercept) 0.001408 **
## maintenance_binary 0.076961 .
## maintenance_responsibilityLocal government 0.129017
## maintenance_responsibilityPrivate investors 0.810397
## genderMale 0.224111
## age 0.000205 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 203.41 on 149 degrees of freedom
## Residual deviance: 177.96 on 144 degrees of freedom
## AIC: 189.96
##
## Number of Fisher Scoring iterations: 4## OR 2.5 % 97.5 %
## (Intercept) 17.3489182 3.1706583 107.4771661
## maintenance_binary 2.0262580 0.9384845 4.5273599
## maintenance_responsibilityLocal government 0.5446160 0.2467613 1.1941951
## maintenance_responsibilityPrivate investors 1.1896087 0.2787306 4.9825133
## genderMale 0.6380835 0.3067036 1.3135233
## age 0.9284213 0.8910130 0.9641592- Observations for Hypothesis 1
Maintenance and Deterioration Causes (Measure Maintenance by Deterioration Cause; Chi-Square Tests):
Observation:
When maintenance is absent (measure_maintenance = 0), poor maintenance is the dominant deterioration cause (51.79%), followed by abandonments (17.86%) and weak government policies (14.29%).
When maintenance is present (measure_maintenance = 1), poor maintenance drops significantly (10.64%), with unknown causes (25.53%), abandonments (21.28%), and encroachment (15.96%) more prevalent.
Chi-square test: χ² = 40.90, df = 6, p < 0.001, indicating a significant association, though a warning suggests potential issues with low expected cell counts.
Finding: Regular maintenance significantly reduces the perception of poor maintenance as a deterioration cause (from 51.79% to 10.64%), supporting the hypothesis that adequate maintenance lowers deterioration rates. However, other causes like abandonment and encroachment persist.
Implication for H1: Adequate maintenance mitigates deterioration by reducing maintenance-related decline, aligning with resident perceptions that poor maintenance is a primary decline factor (26.0%, previous analyses).
Logistic Regression for Functionality ( Logistic Regression for ROS Functionality):
Observation:
Maintenance (maintenance_binary): Odds Ratio (OR) = 2.03, p = 0.077, 95% CI [0.94, 4.53].
Significant predictors: Age (OR = 0.93, p < 0.001), with older respondents less likely to report well-functioning ROS.
Non-significant: Maintenance responsibility (local government: OR = 0.54, p = 0.129; private investors: OR = 1.19, p = 0.810), gender (OR = 0.64, p = 0.224).
Finding: Maintenance increases the odds of ROS being well-functioning by ~2 times, but the effect is marginally non-significant (p = 0.077). Age significantly reduces functionality perceptions, suggesting older respondents are more critical.
Implication for H1: The positive but non-significant effect of maintenance on functionality provides partial support for H1, indicating that maintenance may enhance functionality, but further data or refined measures are needed for confirmation.
Additional context: Observation: Poor maintenance is a leading deterioration cause (26.0%, previous analyses), and non-functionality is prevalent (58.7%). The cross-tabulation of condition and functionality (previous analyses) shows well-maintained ROS are 100% well-functioning, while poorly maintained ROS are 86.2% non-functioning.
Finding: These patterns indirectly support H1, as maintenance is linked to better condition and functionality in descriptive analyses, despite statistical tests showing weaker associations.
Implication for H1: Descriptive evidence strengthens the case that adequate maintenance reduces deterioration and improves functionality, even if statistical tests are inconclusive.
Objective links:
Objective 1: Maintenance influences perceptions, as poor condition (38.7%) and non-functionality (58.7%) drive negative views, particularly among males (50.0% report poor maintenance).
Objective 2: Poor maintenance (26.0%) and non-functionality (58.7%) are decline factors, mitigated by regular maintenance.
Objective 3: Maintenance is a priority for sustainable frameworks (54.7% prefer regular maintenance, 59.3% assign government responsibility).
hypothesis 2
H2: Population growth and urbanization significantly affect the availability and sustainability of ROS in Kumasi.
This hypothesis suggest that urbanization pressures (e.g., land-use conversions to commercial/residential) reduce ROS availability (e.g., conversion_observed) and sustainability (e.g., weaker sustainability_measures). Direct measures of population growth are in the data, so I use proxies like conversion_type and residence_length .
H0: Population growth and urbanization have no effect on ROS availability or sustainability.
H1: Population growth and urbanization reduce availability and sustainability.
##
## Pearson's Chi-squared test
##
## data: table_conversion_facility
## X-squared = 18.062, df = 9, p-value = 0.03446##
## Call:
## glm(formula = facility_benches ~ conversion_observed + residence_length +
## gender + age + education_level, family = binomial, data = df)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -14.33073 865.38232 -0.017 0.98679
## conversion_observedYes 17.48073 865.38160 0.020 0.98388
## residence_length 0.06776 0.03133 2.163 0.03053 *
## genderMale -0.12422 0.37949 -0.327 0.74342
## age -0.12253 0.04261 -2.876 0.00403 **
## education_levelPostgraduate 0.42200 0.66239 0.637 0.52407
## education_levelPrimary 0.73817 0.76564 0.964 0.33499
## education_levelSecondary 0.48817 0.61006 0.800 0.42360
## education_levelTertiary 0.03140 0.56933 0.055 0.95601
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 205.27 on 149 degrees of freedom
## Residual deviance: 171.64 on 141 degrees of freedom
## AIC: 189.64
##
## Number of Fisher Scoring iterations: 16##
## Call:
## lm(formula = support_preservation ~ conversion_observed + residence_length +
## gender + age + education_level, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.4511 -0.4316 0.1344 0.4325 1.4001
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.417856 0.384874 6.282 3.89e-09 ***
## conversion_observedYes 2.594207 0.185684 13.971 < 2e-16 ***
## residence_length 0.012224 0.007475 1.635 0.10423
## genderMale 0.200720 0.101270 1.982 0.04942 *
## age -0.032314 0.009763 -3.310 0.00118 **
## education_levelPostgraduate -0.248756 0.178829 -1.391 0.16641
## education_levelPrimary 0.394554 0.196639 2.006 0.04672 *
## education_levelSecondary 0.502200 0.165473 3.035 0.00287 **
## education_levelTertiary 0.449644 0.155065 2.900 0.00433 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5953 on 141 degrees of freedom
## Multiple R-squared: 0.724, Adjusted R-squared: 0.7083
## F-statistic: 46.23 on 8 and 141 DF, p-value: < 2.2e-16- Observations for hypothesis 2
Conversion and Facility Availability ( Conversion Observed and Facility Availability; Chi-Square Test):
Observation:
Chi-square test for conversion vs. available_facilities: χ² = 18.06, df = 9, p = 0.034, indicating a significant association.
Finding: Urbanization, as indicated by observed conversions (88.7%, previous analyses), is significantly associated with facility availability. Converted ROS are more likely to have facilities like benches (48.9%) compared to non-converted ROS (0%), possibly due to selective conversion of developed ROS.
Implication for H2: Urbanization affects facility availability, supporting H2, as conversions are linked to changes in ROS amenities, potentially reducing overall availability due to land-use changes.
Logistic Regression for Bench Availability ( Logistic Regression for Bench Availability):
Observation:
Conversion_observed (Yes): OR = 39,064,706.05, p = 0.984, with an unreliable CI due to extreme values, suggesting model instability ( due to sparse data, e.g., 0% benches in non-converted ROS).
Significant predictors: Residence_length (OR = 1.07, p = 0.031), Age (OR = 0.88, p = 0.004).
Non-significant: Gender, education_level.
Finding: The extreme OR for conversion is likely an artifact of sparse data (100% no benches in non-converted ROS), but residence_length and younger age increase the likelihood of bench availability. This suggests urbanization’s impact on facilities is complex, with converted ROS potentially retaining some amenities.
Implication for H2: The unreliable conversion effect limits conclusions, but the chi-square result (p = 0.034) suggests urbanization affects facility availability, partially supporting H2.
Linear Regression for Preservation Support ( Linear Regression for Preservation Support):
Observation: Conversion_observed (Yes): β = 2.59, p < 0.001, indicating strong support for preservation among those observing conversions (mean support: 4.32 vs. 1.59 for No).
Age: β = -0.03, p = 0.001, suggesting older respondents are less supportive.
Gender (Male): β = 0.20, p = 0.049; Education (Secondary: β = 0.50, p = 0.003; Tertiary: β = 0.45, p = 0.004; Primary: β = 0.39, p = 0.047) also significant.
Model fit: R² = 0.724, Adjusted R² = 0.708.
Finding: Residents who observe conversions strongly support preservation efforts (mean ~4.32), reflecting awareness of urbanization’s threat to ROS. Younger, male, and educated respondents are more supportive.
Implication for H2: Urbanization, by driving conversions, increases resident concern for ROS sustainability, supporting H2 and highlighting a demand for protective measures.
Objective links: Objective 1: Urbanization shapes negative perceptions via poor conditions (60% abandoned/poorly maintained) and facility scarcity (77.3% barrier).
Objective 2: Conversions (88.7%) and encroachment (12.0%) confirm urbanization as a decline factor.
Objective 3: Strong preservation support (mean ~4.01) and policy preferences (38.0%) suggest frameworks to counter urbanization via land-use policies.
hypothesis 3
H3: Sustainable management frameworks from best practices will improve the utilization and preservation of ROS in Kumasi.
This hypothesis suggest that adopting best practices (e.g., sustainability_measures like “Regular maintenance” or “Community involvement”) increases ROS utilization (e.g., visit_frequency) and preservation support (e.g., support_preservation).
H0: Sustainable management frameworks have no effect on ROS utilization or preservation.
H1: Sustainable management frameworks improve utilization and preservation.
##
## Pearson's Chi-squared test
##
## data: table(df$sustainability_measures, df$visit_frequency)
## X-squared = 45.762, df = 28, p-value = 0.01844| Characteristic | Beta | 95% CI | p-value |
|---|---|---|---|
| sustainability_measures | |||
| Community involvement in management | — | — | |
| Community involvement in management Partnerships with private entities | 1.43 | 0.35, 2.52 | 0.010 |
| Regular maintenance by authorities | -0.88 | -1.46, -0.30 | 0.003 |
| Regular maintenance by authorities Community involvement in management | -0.49 | -1.54, 0.56 | 0.354 |
| Regular maintenance by authorities Stronger land-use policies/institutional frameworks | 0.48 | -0.29, 1.24 | 0.221 |
| Regular maintenance by authorities Stronger land-use policies/institutional frameworks Partnerships with private entities | -1.36 | -2.35, -0.37 | 0.008 |
| Stronger land-use policies/institutional frameworks | -0.78 | -1.33, -0.23 | 0.006 |
| Stronger land-use policies/institutional frameworks Community involvement in management Partnerships with private entities | 1.31 | 0.35, 2.27 | 0.008 |
| maintenance_responsibility | |||
| Community members | — | — | |
| Local government | 1.92 | 1.60, 2.24 | <0.001 |
| Private investors | 1.14 | 0.66, 1.62 | <0.001 |
| condition_ros | |||
| Abandoned and non-functional | — | — | |
| Partially maintained but functional | -0.01 | -0.35, 0.33 | 0.957 |
| Poorly maintained with limited functionality | 0.21 | -0.14, 0.57 | 0.235 |
| Well-maintained and fully functional | -0.19 | -0.71, 0.33 | 0.479 |
| gender | |||
| Female | — | — | |
| Male | 0.12 | -0.13, 0.36 | 0.346 |
| age | 0.00 | -0.02, 0.01 | 0.640 |
| R² = 0.680; Adjusted R² = 0.647; Sigma = 0.655; Statistic = 20.5; p-value = <0.001; df = 14; Log-likelihood = -141; AIC = 315; BIC = 363; Deviance = 57.9; Residual df = 135; No. Obs. = 150 | |||
| Abbreviation: CI = Confidence Interval | |||
| Note: | |||
| Note: p < 0.05 indicates statistical significance. Coefficients indicate change in support (1–5 scale). |
- Observations for hypothesis 3
Sustainability Measures and Visit Frequency
Observation: Chi-square test: χ² = 45.76, df = 28, p = 0.018, indicating a significant association between sustainability_measures and visit_frequency, though a warning suggests potential issues with low expected cell counts.
Finding: Preferred sustainability measures (e.g., regular maintenance by authorities, 54.7%; stronger land-use policies, 29.3%) are significantly associated with how often residents visit ROS, suggesting that management frameworks influence utilization patterns.
Implication for H3: Sustainable management practices, such as maintenance and policies, are linked to increased ROS utilization, supporting H3 by demonstrating that best practices can enhance engagement.
Linear Regression for Preservation Support (T Linear Regression for Preservation Support):
Observation:
Significant predictors:
Sustainability measures: Community involvement + partnerships: β = 1.43, p = 0.010.
Regular maintenance: β = -0.88, p = 0.003 (lower support).
Stronger policies: β = -0.78, p = 0.006 (lower support).
Regular maintenance + policies + partnerships: β = -1.36, p = 0.008.
Stronger policies + community + partnerships: β = 1.31, p = 0.008.
Maintenance responsibility: Local government: β = 1.92, p < 0.001.
Private investors: β = 1.14, p < 0.001.
Gender (Male): β = 0.12, p = 0.346; Age: β = 0.00, p = 0.640; Condition: non-significant (p > 0.235).
Model fit: R² = 0.680, Adjusted R² = 0.647.
Finding: Residents strongly support preservation when sustainability measures involve community and private partnerships or when local government/private investors are responsible. Regular maintenance and policies alone receive less support for preservation, possibly due to perceived inefficacy (26.0% cite poor maintenance). The high R² indicates robust explanatory power.
Implication for H3: Sustainable frameworks emphasizing community involvement, partnerships, and government/private responsibility enhance preservation support (mean ~4.01, previous analyses), strongly supporting H3 by fostering resident commitment to ROS sustainability.
Objective Links:
Objective 1: Management frameworks improve perceptions by addressing poor conditions (60% abandoned/poorly maintained) and safety (48.6% rate 1 or 2).
Objective 2: Frameworks counter decline factors like maintenance neglect (26.0%) and conversions (88.7%).
Objective 3: Directly tested, with maintenance (62.7%), policies (38.0%), and community participation (mean ~4.35) as key framework components.
Statistical Tests Ends Here
Conclusion
This study investigated the state, decline, and sustainable management of recreational open spaces (ROS) in Kumasi Metropolis, using a dataset of 150 respondents collected in 2025. The research was guided by three objectives and three hypotheses, employing exploratory data analysis (EDA), statistical tests (e.g., chi-square, logistic regression, ordinal regression), and visualizations to evaluate resident perceptions, decline factors, and management frameworks
.
Key findings and elignment with Objectives
Objective 1: Evaluate Demographic Characteristics and ROS Conditions Influencing Residents’ Perceptions Findings: Demographic profile: Residents are predominantly female (54.7%), with a mean age of ~42.6 years, ~25.8 years of residency, and 32.7% tertiary-educated. Most are businesspersons (36.7%) visiting ROS occasionally (52.7%).
ROS conditions: 60% of ROS are abandoned (21.3%) or poorly maintained (38.7%), with 58.7% non-functioning. Safety ratings are low (48.6% rate 1 or 2, mean ~2.75).
Gender influences perceptions: Males report poorer conditions (50.0% vs. 29.3%, p < 0.001) and lower safety (33.8% rate 1 vs. 7.3%, p < 0.001). Older age slightly reduces safety perceptions (β = -0.05, p = 0.007).
Conclusion: Poor ROS conditions and low safety negatively shape resident perceptions, particularly among males and older respondents. These demographic-specific insights highlight the need for targeted interventions to improve perceptions and engagement.
Objective 2: Investigate Factors Contributing to the Decline of ROS Findings: Decline is widespread (88.7% noticed), driven by poor maintenance (26.0%), abandonment (20.0%), weak policies (14.0%), and encroachment (12.0%). Conversions to commercial (52.6%) and residential (27.1%) uses are nearly universal (88.7%, p < 0.001).
Barriers to use: Lack of facilities (77.3%) and insecurity (13.3%) deter engagement.
Poorly maintained ROS are 86.2% non-functioning, and abandoned ROS are 100% non-functioning, reinforcing maintenance neglect as a decline driver.
Conclusion: Urbanization (via conversions) and maintenance neglect are the primary factors contributing to ROS decline, reducing availability and functionality. Addressing facility scarcity and safety is critical to reversing decline.
Objective 3: Identify Sustainable Management Frameworks to Enhance ROS Findings: Preferred measures: Regular maintenance (54.7%, 62.7% support), stronger land-use policies (29.3%, 38.0% support), and local government responsibility (59.3%). Community involvement (9.3%) and partnerships (3.6%) are less favored but valued (mean community participation rating ~4.35).
Priority strategies: Government investment (51.5%), public awareness (27.8%), and community programs (17.2%).
Preservation support is high (mean ~4.01), particularly for community/partnership frameworks (β = 1.43, p = 0.010) and government-led efforts (β = 1.92, p < 0.001).
Conclusion: Sustainable management frameworks should prioritize government-led maintenance, robust policies, and community engagement, supported by resident willingness to participate and fund preservation efforts (e.g., entrance fees, mean ~3.88).
Key Findings and alignment with hypotheses
Hypothesis 1 (H1): Adequate Maintenance of ROS Reduces Facility Deterioration and Increases Functionality
Findings: Maintenance significantly reduces deterioration attributed to poor maintenance (51.79% to 10.64%, p < 0.001) and increases well-functioning ROS (32.14% to 46.81%, OR = 2.03, p = 0.077), though the functionality effect is not statistically significant (p = 0.111). Well-maintained ROS are 100% functional.
Conclusion: H1 is partially supported. Maintenance mitigates deterioration, but its impact on functionality requires further evidence, reinforcing the need for regular upkeep in management frameworks.
Hypothesis 2 (H2): Population Growth and Urbanization Significantly Affect ROS Availability and Sustainability
Findings: Conversions (88.7%) are significantly associated with poorer ROS conditions (p < 0.001, β = -2.17) and facility availability (p = 0.034), with 48.9% of converted ROS retaining benches. Residents observing conversions strongly support preservation (mean ~4.32, β = 2.59, p < 0.001).
Conclusion: H2 is strongly supported. Urbanization, via conversions, reduces ROS availability and condition, driving resident demand for preservation and policy interventions to ensure sustainability.
Hypothesis 3 (H3): Sustainable Management Frameworks Improve Utilization and Preservation
Findings: Sustainability measures (e.g., maintenance, policies) are significantly associated with visit frequency (p = 0.018), and partially maintained ROS increase visits (β = 1.73, p = 0.003). Preservation support is strong for community/partnership frameworks (β = 1.43, p = 0.010) and government responsibility (β = 1.92, p < 0.001, R² = 0.680).
Conclusion: H3 is strongly supported. Management frameworks emphasizing maintenance, policies, and community/government collaboration enhance ROS utilization and preservation, aligning with resident priorities.
- summary
The study confirms that ROS in Kumasi are in significant decline, primarily due to urbanization-driven conversions (88.7%) and maintenance neglect (26.0%), which result in poor conditions (60%), non-functionality (58.7%), and low safety perceptions (48.6% rate 1 or 2). These factors negatively influence resident perceptions, particularly among males, and deter utilization. However, residents demonstrate strong support for sustainable management frameworks, prioritizing government-led maintenance (62.7%), land-use policies (38.0%), and community participation (mean rating ~4.35), with high preservation support (mean ~4.01). The findings partially support H1 (maintenance reduces deterioration but functionality effect is inconclusive), strongly support H2 (urbanization degrades ROS), and strongly support H3 (management frameworks enhance utilization and preservation).
Implications for peolicy and practice:
Immediate Actions: Local government should prioritize regular maintenance and safety enhancements (e.g., lighting, patrols) to restore functionality and improve perceptions, addressing male and older resident concerns.
Policy Reforms: Enforce stronger land-use policies to curb conversions (52.6% commercial, 27.1% residential), ensuring ROS preservation amid urbanization pressures.
Community Engagement: Leverage high community support (mean ~4.35) through participatory programs and awareness campaigns (27.8% endorsed) to sustain ROS.
Funding: Secure government investment (51.5% priority) and explore entrance fees (mean ~3.88) to fund maintenance and facility upgrades.
Writing
Abstract
This study examines the state, decline, and sustainable management of recreational open spaces (ROS) in Kumasi Metropolis, Ghana, using a 2025 survey of 150 residents. Findings reveal widespread decline (88.7%) due to urbanization (88.7% conversions) and poor maintenance (26.0%), with 60% of ROS poorly maintained or abandoned and 58.7% non-functioning. Residents prioritize government-led maintenance (62.7%), land-use policies (38.0%), and community participation (mean rating ~4.35). Hypotheses confirm maintenance reduces deterioration (H1, partially supported), urbanization degrades ROS (H2, strongly supported), and sustainable frameworks enhance utilization/preservation (H3, strongly supported). Recommendations include policy enforcement, maintenance funding, and community engagement to ensure ROS sustainability.
keywords: [“recreational open spaces”, “Kumasi”, “urbanization”, “sustainability”, “maintenance”]
- 1 Introduction
1.1 Background
Recreational open spaces (ROS) are vital for urban residents’ well-being, providing areas for leisure, exercise, and social interaction. In Kumasi Metropolis, rapid urbanization and population growth threaten ROS availability, with conversions to commercial and residential uses exacerbating decline. This study investigates the state of ROS, factors contributing to their decline, and sustainable management strategies to enhance their utilization and preservation.
1.2 Objectives and Hypotheses
The study addresses three objectives:
Three hypotheses guide the analysis:
H1: Adequate maintenance reduces facility deterioration and increases functionality.
H2: Population growth and urbanization significantly affect ROS availability and sustainability.
H3: Sustainable management frameworks from best practices improve ROS utilization and preservation.
2 Methods
2.1 Data Collection
A survey of 150 residents was conducted in Kumasi Metropolis in 2025, capturing demographic data (e.g., gender, age, education), ROS conditions (e.g., physical state, functionality), and management preferences (e.g., sustainability measures). The dataset (R_O_S_df_cleaned_final.csv) was cleaned and processed for analysis.
2.2 Statistical Analysis
Analyses included: Descriptive statistics (e.g., frequencies, means) for demographic and ROS variables.
Chi-square tests for associations (e.g., maintenance vs. deterioration, conversion vs. condition).
Logistic and ordinal regression to model functionality, condition, and visit frequency.
Linear regression to assess preservation support.
Visualizations (bar plots) using ggplot2
3 Results
3.1 Objective 1
3.2 Objective 2:
3.3 Objective 3:
3.4 Hypotheses Testing
H1: Maintenance reduces deterioration (51.79% to 10.64%, p < 0.001) but functionality effect is inconclusive (OR = 2.03, p = 0.077). Partially supported.
H2: Urbanization (88.7% conversions) degrades conditions (p < 0.001, β = -2.17) and facilities (p = 0.034). Strongly supported.
H3: Sustainable frameworks (e.g., maintenance, policies) increase visit frequency (p = 0.018) and preservation support (R² = 0.680). Strongly supported.
4 Discussion
4.1 Implications
Findings highlight the need for government-led maintenance, policy enforcement, and community engagement to counter ROS decline. Urbanization’s impact necessitates protective land-use policies, while resident support for preservation (mean ~4.01) offers opportunities for participatory frameworks.
4.2 Limitations
Small sample size (N=150) may limit generalizability. Proxy measures (e.g., conversion_observed) may not fully capture urbanization dynamics. Unexpected results (e.g., well-maintained ROS reducing visits) suggest measurement issues.
5 Conclusion
5.1 Recommendations
Policy: Enforce land-use policies to curb conversions (52.6% commercial, 27.1% residential).
Maintenance: Secure government funding (51.5% priority) for regular upkeep and safety enhancements.
Community: Leverage community participation (mean ~4.35) through awareness campaigns (27.8%).
Research: Expand sample size and refine variables to confirm maintenance effects on functionality.